Platform & Architecture

The foundation that keeps the MES running while the plant keeps running

The capabilities describe what VECHR MES does. The platform describes how all of it keeps running, at the scale of a single shop-floor transaction and at the scale of a multi-site deployment, through configuration changes and automation that never stops.

The six foundations behind VECHR MES

FoundationWhat it means in practice
Process OrchestratorA visual flow canvas connecting equipment events to MES transactions, deployable per plant zone, with automatic failover between pods.
Advanced SchedulingFinite-capacity scheduling with Forward, Backward, Leveling, and Drum-Buffer-Rope strategies, using different constraints for each resource type.
AI across the platformFive AI surfaces working in MES context: Insight, Advisor, Expert Engineer, Orchestrator Assistant, and Routing Designer Assistant. All are advisory, and all require human confirmation.
Config PromotionConfiguration changes are promoted through Dev → QA → Prod with a diff before they are applied, rollback, and an audit trail in every environment.
Event-Driven ArchitectureA change from one transaction can be distributed to services, dashboards, OEE, notifications, and other processes without waiting on a batch or a polling interval.
ReliabilityRuns on Kubernetes in the cloud or on-premise, with auto-scaling, self-healing, monitoring, and zero-downtime deployment.

Configuration treated like code

Master data and production configuration are too important to move straight from development into production. VECHR MES brings promotion-pipeline discipline to manufacturing configuration.

  • Dev → QA → Prod Configuration is built in Dev, validated in QA, then promoted to production once the changes have been reviewed.
  • A diff before promotion A comparison between environments shows exactly what will change before the deployment happens.
  • Rollback without rebuilding by hand A problematic promotion can be returned to its previous version without unpicking the changes one at a time.
  • Every move leaves a trail Promotions and rollbacks are recorded per environment, so configuration changes have a history that can be traced.
Dev QA Prod diff diff rollback

Event-driven: one change, many reactions

Production does not wait for a dashboard to refresh. When something changes, the systems that need to know receive the event and can react in their own context.

  • Changes propagate without polling A production event can update OEE, dashboards, notifications, workflows, and related services without waiting for the next batch processing run.
  • Services do not have to know everything about each other Services communicate through events and clear contracts, so adding a new capability does not mean changing every service already running.
  • Grows with the number of lines The same event-driven pattern applies when you add a resource, a production line, a plant, or a new site.

Reliability for a system that cannot merely be "online"

An MES is not an application someone opens when they need a report. It sits in the middle of production execution, so availability, recovery, and the ability to change things without stopping operations are part of the platform design.

PropertyWhat you get
Cloud or on-premiseA Kubernetes-based deployment that can run on AWS, Azure, GCP, or in the company's own data center.
Auto-scaleService capacity can follow changes in load without rebuilding the application architecture.
Self-healingFailed components can be recovered or replaced by the orchestration layer without manual intervention for every instance.
Zero-downtime updatesNew versions can be rolled out progressively, so the platform never has to stop the whole operation.
Built-in monitoringThe health of services, resources, and platform processes can be watched without building an observability layer from scratch.

Scale is not only a machine count

An MES architecture has to grow sideways as well as upward: more resources, more lines, more plants, and more transactions without changing the underlying model.

  • Multi-resource New resources can be added to the plant structure without changing how the system models execution, scheduling, or monitoring.
  • Multi-line and multi-area The ISA-95 structure lets new lines and areas become part of the same model rather than a separate system.
  • Multi-plant Additional plants use the same platform foundation, with access control and configuration still scoped per site.
  • Services can evolve independently A service- and event-based architecture lets new capabilities develop without turning the whole platform into a single monolithic deployment.

AI stays inside platform governance

AI is not a special layer with a privileged route to production data. It follows the same platform rules: read the context it is permitted to read, produce an insight or a draft, then wait for a person before anything is saved.

  • Read for insight AI can answer questions about KPIs, OEE, downtime, orders, batches, and lots from the MES data available to it.
  • Draft for changes Routings, orchestrator flows, or master data changes can be produced as drafts for a person to review.
  • Human confirmation as the gate No AI surface writes a change directly to a production record without human confirmation.
  • Usage can be traced AI consumption can be tracked by user, model, turn, and period, so usage has clear visibility and ownership.

Frequently Asked Questions

What IT, OT, and architecture reviewers usually want settled first.

Can VECHR MES run on-premise?

Yes. The platform is designed to run on Kubernetes, so a deployment can sit in a cloud such as AWS, Azure, or GCP, or in the company's own data center.

Does adding a plant require a different platform?

No. Multi-plant is part of the platform model. Plants, areas, work centers, resource groups, and resources can all be modelled in the same structure, with access control per site.

Is event-driven only used for notifications?

No. Event-driven is the communication pattern between capabilities. A production event can be consumed by OEE, dashboards, notifications, workflows, traceability, and other services as needed.

Can AI change configuration or production data directly?

No. AI surfaces produce insight or drafts. Changes have to pass through human confirmation before they are saved.

How does configuration move from development to production?

Through Config Promotion, Dev → QA → Prod. Every move can be compared through a diff, has a rollback, and is recorded in the audit trail.

Do platform updates require downtime?

The platform is designed to deploy progressively, so updates can be applied without stopping the whole production operation.

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